Comprehensive Evaluation of Regional Sustainable Development Based on Data Envelopment Analysis

An Exploratory DEA and Machine Learning Framework for the Evaluation and Analysis of Sustainability Composite Indicators in the EU

One method that has been proposed for the measurement of sustainability is Data Envelopment Analysis (DEA). Despite its advantages, the method has limitations: First, the efficiency of Decision-Making Units is calculated with weights that are favorable to themselves, which might be unrealistic, and second, it cannot account for different perceptions of sustainability; since there is not an established and unified definition, each analyst can use different data and variations that produce different results. The purpose of the current paper is twofold: (a) to propose an alternative, multi-dimensional DEA model that handles weight flexibility using a different metric (an alternative optimization criterion) and (b) the inclusion of a computational stage that attempts to incorporate different perceptions in the measurement of sustainability and integrates machine learning to explore country sustainability composite indices under different perceptions and assumptions. This approach offers insights in areas such as feature selection and increases the trust in the results by exploiting an inclusive approach to the calculations. The method is used to calculate the sustainability of the 28 EU countries.

Measuring Urban Sustainability over Time at National and Regional Scale for Addressing United Nations Sustainable Development Goal (SDG) 11: Iran and Tehran as Case Studies

It is evident that relations between political conditions and community development have become sophisticated in recent years. More people now live in urbanized areas, and this ongoing urbanization has various ramifications. Many countries are facing swift urban transformation which alters their regional development patterns. Urban sprawl, migration and rural depopulation, regional inequalities, increasing urban poverty, and social injustice are some of these emerging problems. Assessing regional development for identifying the aforementioned predicaments is really imperative and related to the United Nations Sustainable Development Goal (SDG) 11. However, there are limited studies that focus on the assessment of regional sustainable development at both national and regional scales, simultaneously. Thus, this study aims to fill the gap by developing a robust method that can assess and compare the level of sustainability in various regions and at varying scales. This helps to identify areas where urgent prevention or mitigation strategies and action plans are required. In this study, we strived to evaluate Iran’s regions and Tehran’s provinces based on sustainability indicators. To end this, the authors use factor analysis and F’ANP model in both assessments. The results of the study show that Tehran Province was the most developed province, and its F’ANP result was 2.006. Tehran is 10% more sustainable than the third region in the country which is Khorasan Razavi. Isfahan and Khorasan Razavi provinces were in the next in rank with scores of 1.984 and 1.8, respectively. At the bottom of the list, the northern Khorasan, Ilam, and Kohkiloye-Boyerahmad provinces were in the lowest ranked in terms of access to sustainability indices. It is patently obvious that Iran suffers from uneven development, and the majority of border provinces have moderate or bad situations. This uneven development also intensifies migration to Tehran, which already has one-sixth of Iran’s population which has led todeteriorating social inequity and environmental injustice, nationally. The results of the regional assessment of Tehran also show that there is uneven development in Tehran Province. Tehran County is twice as good and sustainable as 68 percent of the counties in this region. The F’ANP result for Tehran County was 0.580, and it has been ranked first over a period due to the exceptional number of facilities in this region. Tehran County became 20% more sustainable during this decade. After Tehran, Firoozkoh and Damavand counties were in the next ranks with scores of 0.389 and 0.343, respectively. Qarchak, Ghods, and Baharestan counties were the weakest based on the sustainability indices, and their F’ANP results were below 0.2.

Land Zoning Management to Achieve Carbon Neutrality: A Case Study of the Beijing–Tianjin–Hebei Urban Agglomeration, China

Land use/cover change (LUCC) has been identified as a crucial driver of changes in the spatiotemporal distribution of carbon dioxide (CO2) emissions. However, few studies have proposed land use optimization to identify key zones for launching ecological engineering projects. Adopting multi-source data and spatial analysis, we estimate the impact of LUCC on CO2 emissions and ecological support capacity. Importantly, the spatial evolution and inequality of carbon sources and sinks are evaluated. The results suggest that (1) the growth of urban areas due to urbanization has exceeded 5293 km2 over the last 18 years and that the number of closed forest areas increased by 1444 km2 while decreases of 16,418, 9437, and 1250 km2 were observed in the water body, cropland, and grassland land-use types, respectively; (2) CO2 levels rose dramatically in the Beijing–Tianjin–Hebei urban agglomeration, increasing from 8.7 × 107 tCO2 in 2000 to 26 × 107 tCO2 in 2018; (3) there is increasing inequality in the emission levels among cities; and (4) the spatial differences in the carbon sink and ecological support capacity are huge. Our findings have the potential to improve the government’s understanding of how to take action to optimize land-use types and how to launch engineering projects in key zones to achieve carbon peak and carbon neutrality, as well as to provide a new perspective for studies on the controls and mitigation of CO2 emissions.

Evolution and the drivers of water use efficiency in the water-deficient regions: a case study on Ω-shaped Region along the Yellow River, China

Enhancement of water use efficiency (WUE) is considered highly important to cope with the water scarcity challenges in dry regions. Therefore, this study evaluated spatiotemporal characteristics of WUE and its related drivers in the Ω-shaped Region along the Yellow River aiming to provide decision support information for alleviating water shortages in this region. We employed the SBM-DEA (slacks-based measure-data envelopment analysis) model to calculate the WUE considering undesired outputs, analyze temporal and spatial variation based on GIS and statistical methods, and investigate the various factors that influence WUE based on the generalized method of moment (GMM) model. The results are as follows. (1) The WUE followed an increasing-decreasing-increasing trend, suggesting that the expanding agricultural and the second industrial structures are largely dominated by water-intensive activities which add further pressure on the water resources. (2) The spatial discrepancy of WUE among the cities is significant; however, the spatial pattern changes were stable during 2010 to 2019. (3) Analysis of influencing factors provides solutions for improving WUE in the Ω-shaped Region. Irrigation system and water conservancy infrastructure development and the acceleration of industrial transformation are necessary for improving the WUE in the Ω-shaped Region.

An Analysis of Agricultural Production Efficiency of Yangtze River Economic Belt Based on a Three-Stage DEA Malmquist Model

The Yangtze River Economic Belt (YREB) is a major national strategic development area in China, and the development of the YREB will greatly promote the development of the entirety China, so research on its agricultural production efficiency is also of great significance. This paper is committed to studying the agricultural production efficiency of 11 provinces in the YREB and adopts a combination of the Data Envelopment Analysis (DEA) model and the Malmquist index to make a dynamic and static analysis on the YREB's agricultural production efficiency from 2010 to 2019. Then, a three-stage DEA Malmquist model that eliminates the factors of random interference and management inefficiency is compared to a model without elimination. The results show that the adjusted technological efficiency changes, technological progress, and total factor productivity increased by -0.1%, 0.24%, and 0.22%, respectively. When comparing these values to the pre-adjustment values, the results indicate that the effect of environmental variables cannot be ignored when studying the agricultural production efficiency of the YREB. At the same time, the differences in the agricultural production efficiency in the YREB are reasonably explained, and feasible suggestions are put forward.

Efficiency Evaluation of Regional Sustainable Innovation in China: A Slack-Based Measure (SBM) Model with Undesirable Outputs

An efficiency evaluation of China’s regional sustainable innovation, evaluating industrial waste and total energy consumption, is the main research subject in this paper. It focuses on a regional measurement and comparison of these undesirable outputs of Chinese firm activities, such as industrial SO2 and CO2 emissions. By applying a data envelopment analysis–slack-based measure (DEA–SBM) model with undesirable outputs indicators, the regional innovation efficiency was evaluated for 30 provinces in China, from 2002 to 2014. The results indicate that the sustainable innovation efficiency of overall China is still relatively low, and varies significantly in different regions. Central and Western China have similar sustainable innovation efficiencies, which are much lower than the sustainable innovation efficiency in Eastern China. Furthermore, the data indicate that regional sustainable innovation efficiency disparities among these three areas are decreasing. Based on these findings, reasons for the sustainable innovation efficiency gap among the different regions were analyzed. To scholars, this paper extends the research on regional sustainable innovation efficiency by implementing an undesirable output perspective to the DEA–SBM model. The findings also provide Chinese policy makers with useful decision support insights for regional sustainable innovation, and energy conservation and emission reduction policies.

Regional environmental regulation efficiency: spatiotemporal characteristics and influencing factors

Research regarding the regional environmental regulation efficiency (ERE) and influencing factors can provide theoretical guidance for regions to improve their ERE effectively. By employing a two-step approach, the data envelopment analysis (DEA) CCR-BCC model is built with the inclusion of scale changes, and a Tobit model is developed to explore the influencing factors for the regional ERE, followed by an application to analyze the spatiotemporal variations of ERE in Jiangsu province from 2005 to 2015. It is found that in time dimension, the ERE lies generally in a weak effective interval of [0.5, 1) and displays a shock upward trend. In the spatial dimension, the ERE presents an obvious "bilateral effect", namely, the efficiency is high for both the southern and northern of Jiangsu province but lower for the middle area. Besides, GDP per capital, industrial structure, trade openness, and population growth are among the main influencing factors of ERE. The findings revealed that temporary short-term policies have noticeable impact on the regional ERE, and "matching effect" between the ERE and regional economic development does not present.

Development of a Composite Measure of Regional Sustainable Development in Indonesia

Sustainable development has been the main agenda for Indonesia’s development at both the national and regional levels. Along with laws concerning the national development plan and regional development that mandate a sustainable development framework, the government has issued President Regulation No. 59/2017 on the implementation of sustainable development goals. The issuance of these recent regulatory frameworks indicates that sustainable development should be taken seriously in development processes. Nevertheless, several factors affect the achievement of sustainable development. This paper investigates how economic, social, and environmental factors could be integrated into regional sustainable development indicators using a new composite index. The index is calculated based on a simple formula that could be useful for practical implementation at the policy level. Three measures of indices are developed: arithmetic, geometric, and entropy-based. The indices are aggregated to be used for comparison purposes among regions in terms of their sustainability performance. Lessons learned are then drawn for policy analysis and several recommendations are provided to address challenges in the implementation stages.

Relevance Analysis of Sustainable Development of China's Yangtze River Economic Belt Based on Spatial Structure

Scientifically justifiable spatial structure can not only promote the efficient use of regional resources, but can also effectively avoid “urban diseases”, such as traffic congestion, housing shortage, resource scarcity, and so on. It is the “regulator” and “booster” of regional development. Firstly, this paper measures the spatial structure of the Yangtze River Economic Belt from the four dimensions of scale distribution, central structure, spatial connection, and compactness: Gini coefficient of urban scale, urban primacy, regional economic linkage strength, and spatial compactness. Secondly, the optimized Super-Slack Based Measure-Undesirable model is used to evaluate the sustainable development status of the Yangtze River Economic Belt. Finally, a sustainable development correlation analysis model based on regional spatial structure is constructed. Based on the overall perspective of the Yangtze River Economic Belt and the individual perspective of 11 provinces and cities, the relationship between the spatial structure of the Yangtze River Economic Belt and sustainable development is analyzed. It is found that the impact of the four spatial structure indicators on the sustainable development level of the Yangtze River Economic Zone is relatively stable in five different periods. The ranking results are as follows: Gini coefficient of urban scale > urban primacy > regional economic linkage strength > spatial compactness.

Behavioral game and simulation analysis of extended producer responsibility system's implementation under environmental regulations

The implementation of the extended producer responsibility (EPR) for e-waste is an important measure to develop an ecological civilization. In order to advance manufacturing enterprises to effectively implement resource and environmental responsibility, this study investigates the main causes of environmental regulation failure from the perspective of government and enterprises. The game theory was used to establish an evolutionary game model between government regulatory departments and electronic and electrical products' manufacturing enterprises. A system dynamic model was utilized to construct the stock-flow graph of the game between government and enterprises, and to carry out simulation analysis under different strategies. The results found that the probability of an enterprise undertaking extended responsibility gradually increased and stabilized with the increase of government supervision and punishment intensity; the government's regulatory probability and punishment are important factors affecting the enterprises' compliance with regulations and responsibilities. The study suggests that government should focus on strengthening environmental regulations from the aspects of improving laws and regulations, establishing a regular monitoring system and innovating incentive and constraint mechanism.

Evaluation of the Supply-Side Efficiency of China’s Real Estate Market: A Data Envelopment Analysis

With the gradual slowdown of economic growth in China, the Chinese government proposed the task of supply-side reform. As a vital part of China’s economy, supply-side reform in the real estate market is particularly important. Using 29 provinces (divided into seven regions) in China as examples, this paper empirically studies the supply-side efficiency of China’s real estate market using data envelopment analysis (DEA) for the period of 2012–2016. The results showed that (1) the main problem of low supply-side efficiency in the Chinese real estate market is the low land-use efficiency, with a redundancy rate of 60.59% in China’s land space pending development; and (2) China’s southeastern coastal region, with the highest supply-side efficiency in the real estate market, reached a level of decreasing returns, and it is no longer appropriate to increase the supply-side efficiency by expanding the market scale. However, the southwestern region and the Yangtze River’s middle region, which both have lower supply-side efficiency, can improve the land utilization ratio and technology investment to change the current situations. The study results suggest (1) improving the construction land development efficiency by adjusting the input and output of the market according to the specific conditions of each city, and (2) promoting the supply-side reform of China’s real estate market and sustainable urbanization.